Test pattern compression for an integrated circuit test environment

ABSTRACT

A method for compressing test patterns to be applied to scan chains in a circuit under test. The method includes generating symbolic expressions that are associated with scan cells within the scan chains. The symbolic expressions are created by assigning variables to bits on external input channels supplied to the circuit under test. Using symbolic simulation, the variables are applied to a decompressor to obtain the symbolic expressions. A test cube is created using a deterministic pattern that assigns values to the scan cells to test faults within the integrated circuit. A set of equations is formulated by equating the assigned values in the test cube to the symbolic expressions associated with the corresponding scan cell. The equations are solved to obtain the compressed test pattern.

RELATED APPLICATION DATA

This application claims the benefit of U.S. Provisional Application No.60/167,446 filed Nov. 23, 1999, which is hereby incorporated byreference.

TECHNICAL FIELD

This invention relates generally to testing of integrated circuits and,more particularly, to the generation and application of test data in theform of patterns, or vectors, to scan chains within acircuit-under-test.

BACKGROUND

As integrated circuits are produced with greater and greater levels ofcircuit density, efficient testing schemes that guarantee very highfault coverage while minimizing test costs and chip area overhead havebecome essential. However, as the complexity of circuits continues toincrease, high fault coverage of several types of fault models becomesmore difficult to achieve with traditional testing paradigms. Thisdifficulty arises for several reasons. First, larger integrated circuitshave a very high and still increasing logic-to-pin ratio that creates atest data transfer bottleneck at the chip pins. Second, larger circuitsrequire a prohibitively large volume of test data that must be thenstored in external testing equipment. Third, applying the test data to alarge circuit requires an increasingly long test application time. Andfourth, present external testing equipment is unable to test such largercircuits at their speed of operation.

Integrated circuits are presently tested using a number of structureddesign for testability (DFT) techniques. These techniques rest on thegeneral concept of making all or some state variables (memory elementslike flip-flops and latches) directly controllable and observable. Ifthis can be arranged, a circuit can be treated, as far as testing ofcombinational faults is concerned, as a combinational network. Themost-often used DFT methodology is based on scan chains. It assumes thatduring testing, all (or almost all) memory elements are connected intoone or more shift registers, as shown in the U.S. Pat. No. 4,503,537. Acircuit that has been designed for test has two modes of operation: anormal mode, and a test or scan mode. In the normal mode, the memoryelements perform their regular functions. In the scan mode, the memoryelements become scan cells that are connected to form a number of shiftregisters called scan chains. These scan chains are used to shift a setof test patterns into the circuit and to shift out circuit, or test,responses to the test patterns. The test responses are then compared tofault-free responses to determine if the circuit-under-test (CUT) worksproperly.

Scan design methodology has gained widespread adoption by virtue of itssimple automatic test pattern generation (ATPG) and silicon debuggingcapabilities. Today, ATPG software tools are so efficient that it ispossible to generate test sets (a collection of test patterns) thatguarantee almost complete fault coverage of several types of faultmodels including stuck-at, transition, path delay faults, and bridgingfaults. Typically, when a particular potential fault in a circuit istargeted by an ATPG tool, only a small number of scan cells, e.g., 2-5%,must be specified to detect the particular fault (deterministicallyspecified cells). The remaining scan cells in the scan chains are filledwith random binary values (randomly specified cells). This way thepattern is fully specified, more likely to detect some additionalfaults, and can be stored on a tester.

Because of the random fill requirement, however, the test patterns aregrossly over-specified. These large test patterns require extensivetester memory to store and a considerable time to apply from the testerto a circuit-under-test. FIG. 1 is a block diagram of a conventionalsystem 18 for testing digital circuits with scan chains. Externalautomatic testing equipment (ATE), or tester, 20 applies a set of fullyspecified test patterns 22 one by one to a CUT 24 in scan mode via scanchains 26 within the circuit. The circuit is then run in normal modeusing the test pattern as input, and the test response to the testpattern is stored in the scan chains. With the circuit again in scanmode, the response is then routed to the tester 20, which compares theresponse with a fault-free reference response 28, also one by one. Forlarge circuits, this approach becomes infeasible because of large testset sizes and long test application times. It has been reported that thevolume of test data can exceed one kilobit per single logic gate in alarge design. The significant limitation of this approach is that itrequires an expensive, memory-intensive tester and a long test time totest a complex circuit.

These limitations of time and storage can be overcome to some extent byadopting a built-in self-test (BIST) framework, as shown in the U.S.Pat. No. 4,503,537. In BIST, additional on-chip circuitry is included togenerate test patterns, evaluate test responses, and control the test.In conventional logic BIST, where pseudo-random patterns are used astest patterns, 95-96% coverage of stuck-at faults can be achievedprovided that test points are employed to address random-patternresistant faults. On average, one to two test points may be required forevery 1000 gates. In BIST, all responses propagating to observableoutputs and the signature register have to be known. Unknown valuescorrupt the signature and therefore must be bounded by additional testlogic. Even though pseudo-random test patterns appear to cover asignificant percentage of stuck-at faults, these patterns must besupplemented by deterministic patterns that target the remaining, randompattern resistant faults. Very often the tester memory required to storethe supplemental patterns in BIST exceeds 50% of the memory required inthe deterministic approach described above. Another limitation of BISTis that other types of faults, such as transition or path delay faults,are not handled efficiently by pseudo-random patterns. Because of thecomplexity of the circuits and the limitations inherent in BIST, it isextremely difficult, if not impossible, to provide a set of specifiedtest patterns that fully covers hard-to-test faults.

Weighted pseudo-random testing is another method that is used to addressthe issue of the random pattern resistant faults. In principle, thisapproach expands the pseudo-random test pattern generators by biasingthe probabilities of the input bits so that the tests needed forhard-to-test faults are more likely to occur. In general, however, acircuit may require a very large number of sets of weights, and, foreach weight set, a number of random patterns have to be applied. Thus,although the volume of test data is usually reduced in comparison tofully specified deterministic test patterns, the resultant testapplication time increases. Moreover, weighted pseudo-random testingstill leaves a fraction of the fault list left uncovered. Details ofweighted random pattern test systems and related methods can be found ina number of references including U.S. Pat. Nos. 4,687,988; 4,801,870;5,394,405; 5,414,716; and 5,612,963. Weighted random patterns have beenprimarily used as a solution to compress the test data on the tester.The generation hardware appears to be too complex to place it on thechip. Consequently, the voluminous test data is produced off-chip andmust pass through relatively slow tester channels to thecircuit-under-test. Effectively, the test application time can be muchlonger than that consumed by the conventional deterministic approachusing ATPG patterns.

Several methods to compress test data before transferring it to thecircuit-under-test have been suggested. They are based on theobservation that the test cubes (i.e., the arrangement of test patternsbits as they are stored within the scan chains of a circuit-under-test)frequently feature a large number of unspecified (don't care) positions.One method, known as reseeding of linear feedback shift registers(LFSRs), was first proposed in B. Koenemann, “LFSR-Coded Test PatternsFor Scan Designs,” Proc. European Test Conference, pp. 237-242 (1991).Consider an _(n)-bit LFSR with a fixed polynomial. Its output sequenceis then completely determined by the initial seed. Thus, applying thefeedback equations recursively provides a system of linear equationsdepending only on the seed variables. These equations can be associatedwith the successive positions of the LFSR output sequence. Consequently,a seed corresponding to the actual test pattern can be determined bysolving the system of linear equations, where each equation representsone of the specified positions in the test pattern. Loading theresultant seed into the LFSR and subsequently clocking it will producethe desired test pattern. A disadvantage of this approach, however, isthat seed, which encodes the contents of the test cube, is limited toapproximately the size of the LFSR. If the test cube has more specifiedpositions than the number of stages in LFSR, the test cube cannot beeasily encoded with a seed. Another disadvantage of this approach is thetime it requires. A tester cannot fill the LFSR with a seed concurrentlywith the LFSR generating a test pattern from the seed. Each of thesesteps must be done at mutually exclusive times. This makes the operationof the tester very inefficient, i.e., when the seed is serially loadedto the LFSR the scan chains do not operate; and when the loading of thescan chains takes place, the tester cannot transfer a seed to the LFSR.

Another compression method is based on reseeding of multiple polynomialLFSRs (MP-LFSRs) as proposed in S. Hellebrand et al., “Built-In Test ForCircuits With Scan Based On Reseeding of Multiple Polynomial LinearFeedback Shift Registers,” IEEE Trans. On Computers, vol. C-44, pp.223-233 (1995). In this method, a concatenated group of test cubes isencoded with a number of bits specifying a seed and a polynomialidentifier. The content of the MP-LFSR is loaded for each test group andhas to be preserved during the decompression of each test cube withinthe group. The implementation of the decompressor involves adding extramemory elements to avoid overwriting the content of the MP-LFSR duringthe decompression of a group of test patterns. A similar technique hasbeen also discussed in S. Hellebrand et al., “Pattern generation for adeterministic BIST scheme,” Proc. ICCAD, pp. 88-94 (1995). Reseeding ofMP-LFSRs was further enhanced by adopting the concept of variable-lengthseeds as described in J. Rajski et al., “Decompression of test datausing variable-length seed LFSRs”, Proc. VLSI Test Symposium, pp.426-433 (1995) and in J. Raj ski et al., “Test Data Decompression forMultiple Scan Designs with Boundary Scan”, IEEE Trans. on Computers,vol. C-47, pp. 1188-1200 (1998). This technique has a potential forsignificant improvement of test pattern encoding efficiency, even fortest cubes with highly varying number of specified positions. The samedocuments propose decompression techniques for circuits with multiplescan chains and mechanisms to load seeds into the decompressor structurethrough the boundary-scan. Although this scheme significantly improvesencoding capability, it still suffers from the two drawbacks notedabove: seed-length limitations and mutually exclusive times for loadingthe seed and generating test patterns therefrom.

Thus, most reseeding methods to date suffer from the followinglimitations. First, the encoding capability of reseeding is limited bythe length of the LFSR. In general, it is very difficult to encode atest cube that has more specified positions than the length of the LFSR.Second, the loading of the seed and test pattern generation therefromare done in two separate, non-overlapping phases. This results in poorutilization of the tester time.

A different attempt to reduce test application time and test data volumeis described in I. Hamzaoglu et al., “Reducing Test Application Time ForFull Scan Embedded Cores,” Proc. FTCS-29, pp. 260-267 (1999). Thisso-called parallel-serial full scan scheme divides the scan chain intomultiple partitions and shifts in the same test pattern to each scanchain through a single scan input. Clearly, a given test pattern mustnot contain contradictory values on corresponding cells in differentchains loaded through the same input. Although partially specified testcubes may allow such operations, the performance of this scheme stronglyrelies on the scan chain configuration, i.e., the number of the scanchains used and the assignment of the memory elements to the scanchains. In large circuits such a mapping is unlikely to assume anydesired form, and thus the solution is not easily scalable. Furthermore,a tester using this scheme must be able to handle test patterns ofdifferent scan chain lengths, a feature not common to many testers.

SUMMARY

A method according to the invention is used to generate a compressedtest pattern to be applied to scan chains in an integrated circuit undertest. The compressed test pattern is stored in an ATE and is applied oninput channels to an integrated circuit being tested. A clock signal isused to synchronize transfer of data (the compressed pattern) from theATE to the integrated circuit. The compressed pattern is decompressed onthe integrated circuit to obtain a test pattern, which is passed to scanchains to test faults within the integrated circuit. The scan chainsinclude a plurality of scan cells (memory elements) coupled togetherthat store the test pattern.

In one aspect, the compressed pattern is created by using a test cubewith only a portion of the scan cells assigned predetermined values. Theremaining scan cells in the test cube may be left unassigned and arefilled with a pseudo-random pattern generated by the decompressor duringtesting. Thus, the ATPG tool generates test vectors without filling the“don't care” positions with random patterns. Symbolic expressions aregenerated that are associated with the scan cells and that are afunction of externally applied input variables. A set of equations isformulated by equating the symbolic expressions to the values assignedto the scan cells. The compressed pattern is created by solving the setof equations using known techniques. To generate the symbolicexpressions, input variables are assigned to bits applied to the inputchannels. Symbolic simulation of the decompressor is used to create thesymbolic expressions as a linear combination of the input variables. Thesymbolic expressions are then assigned to the scan cells within the scanchains.

In another aspect, after solving the equations, new equations can beincrementally appended to the existing set of equations to test anotherfault. The resulting new set of equations may be solved if a solutionexists. If no solution exists, the most recently appended equations aredeleted and another fault is selected. The process of incrementallyappending equations by selecting new faults continues until a limitingcriteria is reached, such as a predetermined limit of unsuccessfulattempts is reached, or a predetermined number of bits in the test cubeare assigned values.

These and other aspects and features of the invention are describedbelow with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a conventional system for testing digitalcircuits with scan chains.

FIG. 2 is a block diagram of a test system according to the inventionfor testing digital circuits using an ATE.

FIG. 3 is a block diagram of a decompressor according to the invention,including a linear finite state machine (LFSM) and phase shifter.

FIG. 4 shows in more detail a first embodiment of the decompressor ofFIG. 3 coupled to multiple scan chains.

FIG. 5 is a flowchart of a method for compressing a test pattern.

FIG. 6 is a flowchart of a method for generating symbolic expressionsused in compressing a test pattern.

FIG. 7 shows an example of symbolic expressions generated using themethod of FIG. 6.

FIG. 8 shows another embodiment of the present invention with inputvariables being applied to the integrated circuit via input channels.

FIG. 9 shows another embodiment of a decompressor.

FIG. 10 shows yet another embodiment of the decompressor.

FIG. 11 is a flowchart of a method for incrementally appending symbolicexpressions for compression.

DETAILED DESCRIPTION

The methods for compacting test patterns as shown and described hereinare implemented in software stored on a computer-readable medium andexecuted on a general-purpose computer. The invention, for example, canbe implemented in computer aided-design tools. For clarity, only thoseaspects of the software germane to the invention are described; productdetails well known in the art are omitted. For the same reason, thecomputer hardware is not described in further detail. It should thus beunderstood that the invention is not limited to any specific computerlanguage, program, or computer.

FIG. 2 is a block diagram of a system 30 according to the invention fortesting digital circuits with scan chains. The system includes a tester21 such as external automatic testing equipment (ATE) and a circuit 34that includes as all or part of it a circuit-under-test (CUT) 24. Thetester 21 provides from storage a set of compressed test patterns 32 ofbits, one pattern at a time, through input channels 40 to the circuit 34such as an IC. A compressed pattern, as will be described, contains farfewer bits than a conventional uncompressed test pattern. A compressedpattern need contain only enough information to recreatedeterministically specified bits. Consequently, a compressed pattern istypically 2% to 5% of the size of a conventional test pattern andrequires much less tester memory for storage than conventional patterns.Additionally, compressed test patterns require much less time totransfer from a tester to a CUT 24.

Unlike in the prior reseeding techniques described above, the compressedtest patterns 32 are continuously provided from the tester 21 to scanchains 26 within the CUT 24 without interruption. As the compressed testpattern is being provided by the tester 21 to the input channels of adecompressor 36 within the circuit 34, the decompressor decompresses thecompressed pattern into a decompressed pattern of bits. The decompressedtest pattern is then applied to the scan chains 26. This application istypically accomplished while the compressed test pattern is beingprovided to the circuit 34. After circuit logic within the CUT 24 isclocked with a decompressed test pattern in the scan chains 26, the testresponse to that pattern is captured in the scan chains and transferredto the tester 21 for comparison with the compressed fault-free referenceresponses 41 stored therein.

In a typical configuration, the decompressor 36 has one output per scanchain 26, and there are more scan chains than input channels to thedecompressor. However, other configurations are also possible in whichthe decompressor outputs are less than or equal to the input channels.The decompressor generates in a given time period a greater number ofdecompressed bits at its outputs than the number of compressed patternbits it receives during the same time period. This is the act ofdecompression, whereby the decompressor 36 generates a greater number ofbits than are provided to it in a given time period.

To reduce the data volume of the test response and the time for sendingthe response to the tester, the circuit 34 can include means forcompressing the test response that is read from the scan chains 26. Onestructure for providing such compression is one or more spatialcompactors 38. The compressed test responses produced by the compactors38 are then compared one by one with compressed reference responses 40.A fault is detected if a reference response does not match an actualresponse.

The providing of a compressed test pattern to a circuit, itsdecompression into a decompressed test pattern, and the application ofthe decompressed test pattern to the scan chains is performedsynchronously, continuously, and substantially concurrently. The rate atwhich each step occurs, however, can vary. All steps can be performedsynchronously at a same clock rate if desired. Or the steps can beperformed at different clock rates. If the steps are performed at thesame clock rate, or if the compressed test patterns are provided anddecompressed at a higher clock rate than at which the decompressed testpatterns are applied to the scan chains, then the number of outputs ofdecompressor 36 and associated scan chains will exceed the number ofinput channels of the decompressor, as in FIG. 2. In this first case,decompression is achieved by providing more decompressor outputs thaninput channels. If the compressed test patterns are provided at a lowerclock rate and decompressed and applied to the scan chains at a higherclock rate, then the number of outputs and associated scan chains can bethe same, fewer, or greater than the number of input channels. In thissecond case, decompression is achieved by generating the decompressedtest pattern bits at a higher clock rate than the clock rate at whichthe compressed test pattern bits are provided.

FIG. 3 is a block diagram of a decompressor according to the invention.The decompressor 36 comprises a linear finite state machine (LFSM) 46coupled, if desired, through its taps 48 to a phase shifter 50. The LFSMthrough the phase shifter provides highly linearly independent testpatterns to the inputs of numerous scan chains in the CUT 24. The LFSMcan be built on the basis of the canonical forms of linear feedbackshift registers, cellular automata, or transformed LFSRs that can beobtained by applying a number of m-sequence preserving transformations.The output of the LFSM is applied to the phase shifter, which ensuresthat the decompressed patterns present within the multiple scan chains26 at any given time do not overlap in pattern (i.e., are out of phase).

The concept of continuous flow decompression described herein rests onthe fact noted above that deterministic test patterns typically haveonly between 2 to 5 % of bits deterministically specified, with theremaining bits randomly filled during test pattern generation. Testpatterns with partially specified bit positions are defined as testcubes, an example of which appears in Table 2 below. These partiallyspecified test cubes are compressed so that the test data volume thathas to be stored externally is significantly reduced. The fewer thenumber of specified bits in a test cube, the better is the ability toencode the information into a compressed pattern. The ability to encodetest cubes into a compressed pattern is exploited by having a fewdecompressor input channels driving the circuit-under-test, which areviewed by the tester as virtual scan chains. The actual CUT 24, however,has its memory elements connected into a large number of real scanchains. Under these circumstances, even a low-cost tester that has fewscan channels and sufficiently small memory for storing test data candrive the circuit externally.

FIG. 4 shows in more detail the decompressor. The LFSM is embodied in aneight stage Type 1 LFSR 52 implementing primitive polynomialh(x)=x⁸+x⁴+x³+x²+1. The phase shifter 50, embodied in a number of XORgates, drives eight scan chains 26, each having eight scan cells (theillustrated scan cells are memory elements each storing 1 bit ofinformation). The structure of the phase shifter is selected in such away that a mutual separation between its output channels C0-C7 is atleast eight bits, and all output channels are driven by 3-input (tap)XOR functions having the following forms:

TABLE 1 $\begin{matrix}{C_{0} = {s_{4} \oplus s_{3} \oplus s_{1}}} & {C_{4} = {s_{4} \oplus s_{2} \oplus s_{1}}} \\{C_{1} = {s_{7} \oplus s_{6} \oplus s_{5}}} & {C_{5} = {s_{5} \oplus s_{2} \oplus s_{0}}} \\{C_{2} = {s_{7} \oplus s_{3} \oplus s_{2}}} & {C_{6} = {s_{6} \oplus s_{5} \oplus s_{3}}} \\{C_{3} = {s_{6} \oplus s_{1} \oplus s_{0}}} & {C_{7} = {s_{7} \oplus s_{2} \oplus s_{0}}}\end{matrix}$

where C_(i) is the ith output channel and S^(k) indicates the kth stageof the LFSR. Assume that the LFSR is fed every clock cycle through itstwo input channels 37 a, 37 b and input injectors 48 a, 48 b (XOR gates)to the second and the sixth stages of the register. The input variables“a” (compressed test pattern bits) received on channel 37 a are labeledwith even subscripts (a₀, a₂, a₄, . . . ) and the variables “a” receivedon channel 37 b are labeled with odd subscripts (a₁, a₃, a₅, . . . ). Asfurther described below in relation to FIG. 5, treating these externalvariables as Boolean, all scan cells can be conceptually filled withsymbolic expressions being linear functions of input variables injectedby tester 21 into the LFSR 52. Given the feedback polynomial, the phaseshifter 50, the location of injectors 48 a, b as well as an additionalinitial period of four clock cycles during which only the LFSR issupplied by test data, the contents of each scan cell within the scanchains 26 in FIG. 4 can be logically determined.

FIG. 5 shows a flowchart of a method for compressing a test pattern. Ina first process block 60, symbolic expressions are generated that areassociated with scan cells. The generated symbolic expressions are basedon symbolic simulation of the decompressor with a continuous stream ofexternal input variables being provided on the input channels to thedecompressor. Concurrently while the input variables are provided to thedecompressor, the decompressor is in its normal mode of operation,wherein the input variables are being decompressed. Typically, scanchains coupled to the decompressor are also loaded concurrently whilethe input variables are applied to the decompressor. FIG. 6 providesfurther details on a technique for generating the symbolic expressionsand is followed by a specific example.

In process block 62 (FIG. 5), a test cube is generated. The test cube isa deterministic pattern of bits wherein each bit corresponds to a scancell in the scan chains. Some of the scan cells are assigned values(e.g., a logic 1 or logic 0), while other scan cells are “don't cares.”The scan cells that are assigned values are used in the compressionanalysis and are represented in the compressed test pattern. Theremaining scan cells that are “don't cares” need not be represented inthe compressed test pattern and are filled with a pseudo-random valuesgenerated by the decompressor.

In process block 64, a plurality of equations is formulated by equatingthe symbolic expressions generated in process block 60 to the valuesassigned to the scan cells in process block 62. Typically, only the scancells that are assigned values are used in formulating the equations. Byusing a reduced number of equations, compression of the test cube can bemaximized. In process block 66, the equations are solved using knowntechniques, such as Gauss-Jordon elimination.

FIG. 6 provides further details on generation of the symbolicexpressions. The generation of the symbolic expressions is typicallycarried out in a simulated environment, although mathematical analysisalso may be used. In process block 70 the decompressor is reset. Forexample, in the decompressor of FIG. 4, the memory elements 0-7 in theLFSR 52 are reset to a logic low. In process block 72, input variablesare assigned to bits on the input channels. For example, during one ormore clock cycles a different input variable may be assigned to eachinput channel. The input variables are applied to the decompressor andcycle through the memory elements within the decompressor in accordancewith the decompressor logic. Using symbolic simulation, the outputs ofthe decompressor as a function of the input variables are determined(process block 74). In particular, symbolic simulation of thedecompressor is performed by operating the decompressor in its normalmode of operation (i.e., decompressing) concurrently with the inputvariables being injected into the decompressor. Additionally, thedecompressor outputs decompressed data concurrently with the injectionof the input variables that is used to fill scan cells within the scanchains. In process block 76, each output expression is assigned to acorresponding scan cell within a scan chain. That is, an association ismade between the expressions and the scan cells.

Thus, for a given structure of a decompressor, a plurality of symbolicexpressions is formed for each scan cell as linear combinations of theinput variables. In this case, a linear expression is characterized bythe set of variables involved. In every one or more clock cycles of thedecompressor (depending on the clocking scheme), a new set of k inputvariables, where k is the number of external inputs, is loaded into theLFSM through the XOR gates. As a result, linear combinations of alreadyinjected variables can be associated with each memory element of theLFSM. Since at the beginning, for every new test pattern thedecompressor is reset, the corresponding expressions associated with thememory elements of the LFSM are empty. In every cycle, a new expressionassociated with a given memory element, called a destination element, ofan LFSM is computed based on the expressions of other memory elementsand input channels, called sources, feeding the given memory element.The particular forms of these expressions depend on functionality,structure or internal connectivity of the LFSM as well as locations ofthe seed variables injection sites.

The same principle of generation of symbolic expressions applies tooutputs of a phase shifter, which implements a linear function of theLFSM memory elements. For all output channels of the phase shiftersimilar symbolic expressions are generated by adding altogether in theGalois field modulo 2 expressions associated with those stages of theLFSM that are used to drive, through the XOR function, successiveoutputs of the phase shifter. The resultant expressions are subsequentlylinked with successive cells of scan chains driven by these decompressoroutputs. The linking is done at times that exactly correspond to theshifting of scan chains. If the decompressor and the scan chains operateat the same frequency, the output expressions are computed for everycycle of the decompressor operation. If the scan chains work at afrequency that is a sub-multiple of that of the decompressor, thedecompressor equations are computed in every clock cycle, however thescan cell equations are computed only for those cycles that correspondto shift. This operation allows higher transfer rate to the decompressorwhile reducing the power dissipation in the circuit under test. The scanchains may further be divided into several groups with separate shiftclocks to allow independent shift operation. In this case thecomputation of symbolic expressions mimic exactly the circuit operation.

FIG. 7 gives the expressions for the 64 scan cells in FIG. 4, with thescan chains numbered 0 through 7 in FIG. 4 corresponding to the scanchains C7, C1, C6, . . . identified in FIG. 4. The expressions for eachscan chain in FIG. 4 are listed in the order in which the information isshifted into the chain, i.e., the topmost expression represents the datashifted in first. The input variables a₀, a₂, a₄, . . . are assigned tothe input channel 37 a, while a₁, a₃, a₅,. . . are assigned to 37b.Given the decompressor logic, the outputs of the decompressor aredetermined as a function of the input variables, as shown in FIG. 7. Inthe illustrated example, each clock cycle the output of the decompressoris loaded into the scan chains. Consequently, each scan cell has anequation associated with it.

Either before or after the generation of the symbolic expressions, atest cube is generated. The test cube is a deterministic pattern basedon the fault being tested. Assume that the decompressor 36 in FIG. 4 isto generate a test pattern based on the following partially specifiedtest cube in Table 2 (the contents of the eight scan chains are shownhere horizontally, with the leftmost column representing the informationthat is shifted first into the scan chains):

TABLE 2 $\begin{matrix}x & x & x & x & x & x & x & x & {{scan}\quad {chain}\quad 0} \\x & x & x & x & x & x & x & x & {{scan}\quad {chain}\quad 1} \\x & x & x & x & 1 & 1 & x & x & {{scan}\quad {chain}\quad 2} \\x & x & 0 & x & x & x & 1 & x & {{scan}\quad {chain}\quad 3} \\x & x & x & x & 0 & x & x & 1 & {{scan}\quad {chain}\quad 4} \\x & x & 0 & x & 0 & x & x & x & {{scan}\quad {chain}\quad 5} \\x & x & 1 & x & 1 & x & x & x & {{scan}\quad {chain}\quad 6} \\x & x & x & x & x & x & x & x & {{scan}\quad {chain}\quad 7}\end{matrix}$

The variable x denotes a “don't care” condition. The compressed testpattern is determined by equating the equations of FIG. 7 with theassigned bits in the test cube. Then a corresponding compressed testpattern can be determined by solving the following system of tenequations from FIG. 7 using any of a number of well-known techniquessuch as Gauss-Jordan elimination techniques. The selected equationscorrespond to the deterministically specified bits:

TABLE 3 $\begin{matrix}{{{a2} \oplus {a6} \oplus {a11}} = 1} \\{{{a0} \oplus {a1} \oplus {a4} \oplus {a8} \oplus {a13}} = 1} \\{{{a4} \oplus {a5} \oplus {a9} \oplus {a11}} = 0} \\{{{a0} \oplus {a2} \oplus {a5} \oplus {a12} \oplus {a13} \oplus {a17} \oplus {a19}} = 1} \\{{{a1} \oplus {a2} \oplus {a4} \oplus {a5} \oplus {a6} \oplus {a8} \oplus {a12} \oplus {a15}} = 0} \\{{{a0} \oplus {a1} \oplus {a3} \oplus {a5} \oplus {a7} \oplus {a8} \oplus {a10} \oplus {a11} \oplus {a12} \oplus {a14} \oplus {a18} \oplus {a21}} = 1} \\{{{a2} \oplus {a3} \oplus {a4} \oplus {a9} \oplus {a10}} = 0} \\{{{a0} \oplus {a1} \oplus {a2} \oplus {a6} \oplus {a7} \oplus {a8} \oplus {a13} \oplus {a14}} = 0} \\{{{a3} \oplus {a4} \oplus {a5} \oplus {a6} \oplus {a10}} = 1} \\{{{a0} \oplus {a1} \oplus {a3} \oplus {a7} \oplus {a8} \oplus {a9} \oplus {a10} \oplus {a14}} = 1}\end{matrix}$

It can be verified that the resulting seed variables a₀, a₁, a₂, a₃ anda₁₃ are equal to the value of one while the remaining variables assumethe value of zero. This seed will subsequently produce a fully specifiedtest pattern in the following form (the initial specified positions areunderlined):

TABLE 4 $\begin{matrix}1 & 0 & 1 & 0 & 0 & 1 & 0 & 0 \\1 & 1 & 0 & 0 & 0 & 1 & 0 & 0 \\1 & 1 & 1 & 1 & 1 & 1 & 1 & 0 \\0 & 0 & 0 & 1 & \overset{\_}{0} & \overset{\_}{0} & 1 & 1 \\1 & 0 & \overset{\_}{1} & 0 & 0 & 0 & \overset{\_}{0} & 1 \\1 & 1 & 0 & 1 & \overset{\_}{0} & 0 & 0 & \overset{\_}{0} \\1 & 1 & \overset{\_}{1} & 1 & \overset{\_}{1} & 1 & 1 & 1 \\0 & 1 & \overset{\_}{0} & 0 & \overset{\_}{1} & 1 & 0 & 0\end{matrix}$

As can be observed, the achieved compression ratio (defined as thenumber of scan cells divided by the number of compressed pattern bits)is 64/ (2×8+2×4)≈2.66. The fully specified test pattern is thencompressed into a compressed pattern of bits using any of a number ofknown methods The unspecified bits are filled in with pseudo-randomvalues in accordance with the logic of the decompressor.

FIG. 8 shows another representation of the compression process. Moreparticularly, the decompressor includes an LFSM 80 and an associatedlinear phase shifter 82. The LFSM is fed by a number of external inputschannels 84, while the phase shifter is comprised of an XOR networkemployed to avoid shifted versions of the same data in its variousoutput channels (scan chains 26). The LFSM can drive a large number ofscan chains despite that it is relatively small. The phase shifter 82provides a linear combination of the LFSM stage outputs. The LFSMgenerates a sequence with the desired separation from other sequences byemploying the “shift-and-add” property according to which the sum of anysequence produced by the LFSM and a cyclic shift of itself is anothercyclic shift of this sequence. As can be seen in FIG. 8, particular scancells are assigned predetermined values, while other scan cells are“don't cares” as indicated by an “x”. Only scan cells that are assignedpredetermined values are equated with a symbolic expression.

FIG. 9 shows a decompressor and phase shifter and is used to illustratethe derivation of symbolic expressions. The decompressor includes an8-bit LFSM and a corresponding 4-output phase shifter. The architectureof the LFSM has been obtained by transforming an 8-bit linear feedbackshift register implementing primitive polynomial x⁸+x⁶+x⁵+x+1. The inputvariables a₁, a₂, . . . , a₁₄ are provided in pairs through two externalinputs connected by means of the XOR gates to inputs of memory elements1 and 5, respectively. The phase shifter consists of four XOR gatesconnected to the outputs of the LFSM. In the illustrated embodiment, itis desirable that the output expressions are not generated until allmemory elements of the LFSM are filled with at least one input variable.Typically, the number of cycles required to load the LFSM variesdepending on the design. For example, the number of cycles to load theLFSM may depend on the LFSM and the number of input channels, but othercriteria may be used. As illustrated in Table 5, in the illustratedembodiment, all of the memory elements are filled after four consecutiveclock cycles. Continued operation of the decompressor yields theexpressions gathered in the second part of Table 5 (starting on the 5^(th) cycle). Expressions produced on the outputs of the phase shiftersince then are presented in Table 6. New seed variables are injectedinto the LFSM in parallel to, or concurrently with, the scan cells beingfilled.

TABLE 5 7 6 5 4 3 2 1 0 0 0 a₁ 0 0 0 a₂ 0 0 0 a₃ a₁ 0 0 a₄ a₂ a₂ 0 a₅ a₂⊕ a₃ a₁ 0 a₆ a₄ a₄ a₂ a₇ a₄ ⊕ a₅ a₂ ⊕ a₃ a₁ a₈ a₆ a₆ a₂ ⊕ a₄ a₂ ⊕ a₉ a₆⊕ a₇ a₄ ⊕ a₅ a₂ ⊕ a₁ ⊕ a₁₀ a₈ a₃ a₈ a₂ ⊕ a₄ ⊕ a₆ a₂ ⊕ a₄ ⊕ a₂ ⊕ a₈ ⊕ a₆⊕ a₇ a₄ ⊕ a₂ ⊕ a₃ ⊕ a₁ ⊕ a₁₀ a₁₁ a₉ a₅ a₁₂ a₁ ⊕ a₂ ⊕ a₄ ⊕ a₆ a₂ ⊕ a₄ ⊕a₆ a₁ ⊕ a₂ ⊕ a₂ ⊕ a₈ ⊕ a₆ ⊕ a₄ ⊕ a₅ ⊕ a₂ ⊕ a₃ ⊕ a₁₀ ⊕ a₈ ⊕ a₁₃ a₄ ⊕ a₁₀⊕ a₉ a₇ a₁₄ a₁₂ a₁₁

Once the symbolic expressions are determined, a system of equations isformulated for each test cube. These equations are obtained by selectingthe symbolic expressions corresponding to specified positions of thetest cubes (they form the left-hand sides of the equations) andassigning values of these specified positions to the respectiveexpressions. Thus, the right-hand sides of the equations are defined bythe specified positions in the partially specified test patterns. As canbe seen, the process of finding an appropriate encoding of a given testcube is equivalent to solving a system of linear equations in the Galoisfield modulo 2. Solving the equations can be carried out veryefficiently using Gauss - Jordan elimination by taking advantage of fastbit-wise operations. If the system of linear equations has a solution,it can be treated as a compressed test pattern, i.e. having the propertythat when provided to the decompressor yields the decompressed testpattern consistent with the initial, partially specified test vector. Inorder to increase probability of successful encoding, it is desirable togenerate test cubes with the smallest achievable number of specifiedpositions. Consequently, it will reduce the number of equations whilemaintaining the same number of input variables, and thus increasinglikelihood of compression.

TABLE 6 3 2 1 0 a₂ ⊕ a₄ ⊕ a₆ a₂ ⊕ a₆ ⊕ a₉ a₂ ⊕ a₃ ⊕ a₄ ⊕ a₅ ⊕ a₆ ⊕ a₇ a₄⊕ a₅ ⊕ a₈ a₂ ⊕ a₄ ⊕ a₆ ⊕ a₈ a₂ ⊕ a₄ ⊕ a₈ ⊕ a₁₁ a₂ ⊕ a₄ ⊕ a₅ ⊕ a₆ ⊕ a₇ ⊕a₈ ⊕ a₁ ⊕ a₆ ⊕ a₇ ⊕ a₉ a₁₀ a₁ ⊕ a₂ ⊕ a₄ ⊕ a₆ a₁ ⊕ a₂ ⊕ a₄ ⊕ a₆ ⊕ a₁₀ a₁⊕ a₄ ⊕ a₆ ⊕ a₇ ⊕ a₈ ⊕ a₉ ⊕ a₃ ⊕ a₈ ⊕ a₉ ⊕ a₈ ⊕ a₁₀ ⊕ a₁₃ a₁₀ ⊕ a₁₁ a₁₂

For the sake of illustration, consider an example 8-bit decompressorwith two external inputs that drives four 10-bit scan chains as shown inFIG. 10. If this circuit is to generate a test pattern based on thefollowing partially specified test cube (the contents of the four scanchains are shown here horizontally) shown in Table 7:

TABLE 7 x x x x x x x x x x x x x ¹ ¹ x ⁰ x x ¹ x x ⁰ x x ¹ x x ⁰ ⁰ x ¹x ¹ x x x x x x

where x denotes a “don't care” condition, then a correspondingcompressed pattern can be determined by solving the following system ofequations (resulting from the structure of the decompressor of FIG. 9)shown in Table 8:

TABLE 8 ${\begin{matrix}{{{a1} \oplus {a2} \oplus {a5} \oplus {a8} \oplus {a9} \oplus {a11}} = 0} \\{{a5} \oplus {a6} \oplus {a7} \oplus {a9} \oplus {a10} \oplus {a11} \oplus {a12} \oplus {a13} \oplus {a15} \oplus {a18} \oplus {a19} \oplus {a20} \oplus} \\{{a21} \oplus {a23} \oplus} \\{{a24} = 1} \\{{a0} \oplus {a1} \oplus {a3} \oplus {a4} \oplus {a5} \oplus {a6} \oplus {a7} \oplus {a9} \oplus {a12} \oplus} \\{{{a13} \oplus {a14} \oplus {a15} \oplus {a17} \oplus {a18}} = 0} \\{{{a0} \oplus {a1} \oplus {a3} \oplus {a6} \oplus {a7} \oplus {a8} \oplus {a9} \oplus {a11} \oplus {a12}} = 1} \\{{{a0} \oplus {a1} \oplus {a2} \oplus {a3} \oplus {a5} \oplus {a8} \oplus {a9} \oplus {a10} \oplus {a11} \oplus {a13} \oplus {a14}} = 1} \\{{{a0} \oplus {a1} \oplus {a2} \oplus {a3} \oplus {a4} \oplus {a5} \oplus {a6} \oplus {a11} \oplus {a12}} = 1} \\{{{a0} \oplus {a1} \oplus {a2} \oplus {a7} \oplus {a8}} = 1} \\{{{a4} \oplus {a5} \oplus {a7} \oplus {a8} \oplus {a11} \oplus {a14} \oplus {a15} \oplus {a17}} = 1} \\{{{a1} \oplus {a4} \oplus {a5} \oplus {a12} \oplus {a13} \oplus {a15} \oplus {a16} \oplus {a19} \oplus {a22} \oplus {a23} \oplus {a25}} = 0} \\{{{a2} \oplus {a3} \oplus {a10} \oplus {a11} \oplus {a13} \oplus {a14} \oplus {a17} \oplus {a20} \oplus {a21} \oplus {a23}} = 0}\end{matrix}}$

It can be verified that the resulting input variables a₂, a₃, a₅, a₆ anda₁₂ are equal to the value of one while the remaining variables assumethe value of zero. This seed will subsequently produce a fully specifiedtest pattern in the following form (the initial specified position arenow underlined) shown in Table 9:

TABLE 9 0 1 1 1 0 1 1 0 0 0 0 1 0 1 1 0 0 0 0 1 1 0 0 {overscore (1)}{overscore (1)} 1 {overscore (1)} 1 0 {overscore (0)} 0 1 {overscore(0)} 1 0 {overscore (1)} 1 1 {overscore (1)} {overscore (0)}

Furthermore, compression of test patterns is conducted using the ATPGalgorithm that targets multiple faults using the information aboutavailable encoding space. In one form of the present invention, thefaults are selected in such a way that there is no overlap in theassigned inputs. If assignments for a particular fault cannot be found,the encoding space is completely relieved and applied towards anotherfault. In the second form, cones of excitation can overlap and shareassignments. In either case, generation of a test cube for a given faultis followed by the attempt to solve a current set of equations as shownabove.

In order to further enhance the efficiency of the compression, anincremental mode is enabled in which new equations for a next targetedfault are appended to the already existing system of equations.Consequently, steps are not repeated for previous faults covered by thesame test cube. In fact, it keeps carrying out Gauss-Jordan eliminationby utilizing information available from the previous steps. If asolution still exists, the ATPG capable of generating incremental testcube for a subsequent fault is invoked. Otherwise, the recentlygenerated input assignments are canceled and another fault is targetedunless a certain limit of unsuccessful attempts has been reached. In thelatter case, a new test cube is created with the corresponding set oflinear equations.

FIG. 11 is a flowchart of a method illustrating the incremental mode ofcompression. In process block 90, a fault is selected and a test cube isgenerated to test the selected fault. As described previously, the testcube generation is accomplished using a deterministic test pattern. Inprocess block 92, the test cube is used to generate a set of equationsas previously described. In block 94, a determination is made whetherthe equations are solvable. If the equations are solvable, in processblock 96, the set of equations is incrementally appended with one ormore new equations that test one or more other faults. Then adetermination is made whether the set of appended equations is solvableas shown by arrow 98. This process continues until the attempt to solvethe set of equations fails. Upon a failed attempt to solve theequations, process block 94 is answered in the negative causing controlto pass to process block 100. As a result, in process block 100, themost recently appended equation or equations are deleted. In processblock 102, a determination is made whether a limiting criteria has beenreached, such as the number of failures has equaled or exceeded apredetermined threshold, or a number of specified bits in a test cube isreached. For example, if the number of bits in the test cube that areassigned values reaches 90% or 95% of the number of input variables, theincremental appending can be terminated. Any desired limiting criteriamay be used. If the limiting criteria is reached, the final compressedpattern is created (process block 104). If not, process block 96 isagain attempted to incrementally append the equations to test yetanother fault.

Having illustrated and described the principles of the invention inexemplary embodiments, it should be apparent to those skilled in the artthat the illustrative embodiments can be modified in arrangement anddetail without departing from such principles. For example, although thedecompressor is shown as being on the integrated circuit, it may also beon an ATE. In such a case, the input variables are supplied externallyto the decompressor concurrently while the decompressor is operated togenerate the output expressions of the decompressor. Additionally,although the generation of symbolic expressions is shown using symbolicsimulation of a decompressor, such generation can be accomplished bytechniques other than simulation, such as by representing thedecompressor mathematically (e.g., a primitive polynomial) andgenerating the expressions using mathematical analysis. In view of themany possible embodiments to which the principles of the invention maybe applied, it should be understood that the illustrative embodiment isintended to teach these principles and is not intended to be alimitation on the scope of the invention. We therefore claim as ourinvention all that comes within the scope of the following claims andtheir equivalents.

We claim:
 1. A method that computes a compressed test pattern to test anintegrated circuit, comprising: generating symbolic expressions that areassociated with scan cells within an integrated circuit, the symbolicexpressions being a function of input variables applied concurrentlywhile the scan cells are being loaded; generating a test cube havingonly a portion of the scan cells assigned predetermined values;formulating a set of equations by equating the assigned values in thescan cells to the symbolic expressions; and solving the equations toobtain the compressed test pattern.
 2. The method of claim 1, whereinthe values assigned to the scan cells are chosen to test potentialfaults in the integrated circuit.
 3. The method of claim 1, furtherincluding storing the compressed test pattern in an ATE and transferringthe compressed test pattern to an integrated circuit being tested,wherein the integrated circuit includes a decompressor.
 4. The method ofclaim 1, further including, after solving the equations, incrementallyappending the set of equations with one or more equations.
 5. The methodof claim 4, further including: (a) attempting to solve the appended setof equations; (b) if the attempt to solve the equations fails, deletingthe most recently appended equations and appending one or more differentequations onto the set of equations; and (c) if the attempt to solve theequations is successful, incrementally appending additional equationsonto the set of equations; (d) repeating (a)-(c) until a predeterminedlimiting criteria is reached.
 6. The method of claim 1, whereingenerating symbolic expressions includes: assigning the input variablesto bits on input channels to the integrated circuit, wherein the numberof input variables is larger than the number of channels; simulating theapplication of the input variables to a decompressor in the integratedcircuit and simulating that the decompressor is continually clocked todecompress the input variables, wherein one or more additional inputvariables are injected into the decompressor during one or more clockcycles; and generating a set of output expressions from the decompressorthat results from the simulation, wherein the output expressions arebased on the input variables that are injected as the decompressor iscontinually clocked.
 7. The method of claim 6, further includingassigning each of the output expressions to each scan cell within a scanchain in the integrated circuit.
 8. The method of claim 1, whereinsolving the equations includes performing a Gauss-Jordon eliminationmethod for solving equations.
 9. The method of claim 1, whereingenerating a test cube includes assigning values of a predeterminedlogic 1 or a predetermined logic 0 to the scan cells for testing a faultin the integrated circuit.
 10. The method of claim 1, further including:(a) applying the compressed test pattern to the integrated circuit; (b)decompressing the test pattern; and (c) loading scan cells within theintegrated circuit with the decompressed test pattern; (d) wherein (a),(b) and (c) occur substantially concurrently.
 11. The method of claim 1,wherein formulating the set of equations includes: associating eachsymbolic expression in a one-to-one relationship with a scan cell; andfor each scan cell having a predetermined assigned value, equating thesymbolic expression associated with that scan cell to the predeterminedassigned value.
 12. The method of claim 1, wherein generating symbolicexpressions includes using simulation of a decompressor.
 13. The methodof claim 1, wherein generating symbolic expressions includes using amathematical representation of a decompressor.
 14. A method thatcomputes a compressed test pattern used to load scan cells within anintegrated circuit to test for faults, comprising: providing adecompressor having one or more input injectors; assigning inputvariables to bits applied serially to the one or more input injectors;and generating a compressed test pattern by using symbolic expressionsassociated with the scan cells, wherein the symbolic expressions includelinear combinations of the input variables that are applied concurrentlyto the decompressor as the decompressor decompresses the inputvariables.
 15. The method of claim 14, wherein the decompressor includesa linear finite state machine coupled to a phase shifter.
 16. The methodof claim 14, wherein the input injectors include XOR gates.
 17. Themethod of claim 14, wherein the decompressor changes state in responseto a clock signal and during one or more clock cycles a new set of inputvariables are received on the input injectors to the decompressor. 18.The method of claim 14, wherein the decompressor includes multiplememory elements connected together with linear logic gates.
 19. Themethod of claim 14, further including: positioning the decompressorwithin an integrated circuit; providing scan chains within an integratedcircuit, each scan chain comprising multiple scan cells coupled inseries, the scan chains coupled to the decompressor; and generating atest cube that assigns predetermined values to some of the scan cells inorder to test faults within the integrated circuit.
 20. The method ofclaim 14, wherein generating a compressed test pattern includes:generating a test cube having a portion of the scan cells assignedvalues; formulating a set of equations by equating the assigned valuesin the scan cells to the symbolic expressions; and solving the equationsto obtain the compressed test pattern.
 21. The method of 20, furtherincluding incrementally appending the set of equations with one or moreequations.
 22. The method of claim 21, further including terminating theincremental appending if the equations cannot be solved and a limitingcriteria is met or exceeded.
 23. The method of claim 20, furtherincluding attempting to solve the equations and if the equations cannotbe solved, deleting the incrementally appended equations andincrementally appending one or more other equations.
 24. The method ofclaim 14, wherein only bits necessary to create the predetermined valuesin the scan cells are stored in an ATE, while the remaining bits in thescan cells are filled by patterns created in the decompressor.
 25. Themethod of claim 14, further including loading the scan cellsconcurrently as the input variables are applied to the decompressor. 26.The method of claim 14 wherein the decompressor is located on an ATE.27. An apparatus that computes a compressed test pattern to test anintegrated circuit, comprising: means for generating symbolicexpressions that are associated with scan cells within the integratedcircuit, the symbolic expressions associated with loading a decompressorwith externally applied input variables currently as the decompressorcontinually decompresses; means for generating a test cube having only aportion of the scan cells assigned predetermined values; means forformulating a set of equations by equating the assigned values in thescan cells to the symbolic expressions; and means for solving theequations to obtain the compressed test pattern.
 28. A computer-readablemedium on which is stored computer-readable instructions for performingthe following: providing a decompressor having one or more inputinjectors; assigning input variables to bits applied serially to the oneor more input injectors; and generating a compressed test pattern thatuse symbolic expressions associated with the scan cells, wherein thesymbolic expressions include linear combinations of the input variablesapplied concurrently to the input injectors as the decompressorcontinually operates in its normal mode of operation.
 29. A method thatcomputes a compressed test pattern to test an integrated circuit,comprising: using simulation, generating symbolic expressions that areassociated with simulated scan cells of an integrated circuit, thesymbolic expressions being a function of simulated input variablesapplied concurrently to a simulated decompressor, which is coupled tothe scan cells, while the decompressor continually decompresses;generating a test cube having only a portion of the scan cells assignedpredetermined values; formulating a set of equations by equating theassigned values in the scan cells to the symbolic expressions; andsolving the equations to obtain the compressed test pattern.
 30. Themethod of claim 29, wherein the decompresses loads the simulated scancells concurrently while the input variables are applied to thedecompressor.